Authors: Kai Yang; Eliza Yingzi Du
Addresses: Department of Electrical and Computer Engineering, Indiana University-Purdue University, Indianapolis, USA ' Department of Electrical and Computer Engineering, Indiana University-Purdue University, Indianapolis, USA
Abstract: Iris is tested to be the most accurate one. However, most existing methods are not designed for non-cooperative users and cannot work with off-angle or low quality iris images. In this paper, we propose a robust multi-stage feature extraction and matching approach for non-cooperative iris recognition. We developed the Speed Up Robust Feature (SURF)-like method to extract stable feature points, used Gabor Descriptor method for local feature description, and designed the multi-stage feature extraction and matching scheme to improve the recognition accuracy and speed. The experimental results show that the proposed method can not only improve the process speed but also achieve better recognition accuracy.
Keywords: iris recognition; multistage feature extraction; feature matching; biometrics; non-cooperative users; uncooperative users; image quality; process speed; recognition accuracy.
International Journal of Biometrics, 2012 Vol.4 No.4, pp.406 - 421
Received: 07 Nov 2011
Accepted: 23 Feb 2012
Published online: 29 Nov 2014 *